There are 0 repository under weight-pruning topic.
Learning Efficient Convolutional Networks through Network Slimming, In ICCV 2017.
A research library for pytorch-based neural network pruning, compression, and more.
[ICCV2023 Official PyTorch code] for Iterative Soft Shrinkage Learning for Efficient Image Super-Resolution
Image captioning with weight pruning in PyTorch
(Unstructured) Weight Pruning via Adaptive Sparsity Loss
Feather is a module that enables effective sparsification of neural networks during training. This repository accompanies the paper "Feather: An Elegant Solution to Effective DNN Sparsification" (BMVC2023).
TensorFlow implementation of weight and unit pruning and sparsification
Neural network weights prune in a static LoRA–like way
Implementation of several neural network compression techniques (knowledge distillation, pruning, quantization, factorization), in Haiku.
Code Implementation of On Model Compression for Neural Networks: Framework, Algorithm, and Convergence Guarantee
Code for "Characterising Across Stack Optimisations for Deep Convolutional Neural Networks"
Implementation of Neuron Pruning with weight pruning
Pruning is <3
analysing Model Pruning and Unit Pruning on a large dense MNIST network